RCUK-CIAT Newton Fund Advancing sustainable forage-based livestock production systems using multi-source remote sensing and social science approaches

农业和畜牧业生产历来是哥伦比亚经济发展的主要组成部分之一，就农业用地扩展潜力而言，它是世界上最大的国家之一。约34%的土地面积(约4000万公顷)用于畜牧业活动，大多数牧场专门用于广泛的放牧系统。农业是哥伦比亚农村就业的重要来源，也是受气候和气候变化影响最大的部门之一，需要解决影响牧场和畜牧业生产力和可持续性的关键挑战。这一由格拉斯哥大学(UofG)、布里斯托尔大学(UofB)和CIAT合作的项目将汇集跨学科的观点和方法，以开发基于遥感的方法，用于地方和区域层面的牧草监测和管理。其具体目标是：1)制定共同设计的工作流程，用于获取、处理和分析CIAT总部试验场的多维多光谱和雷达数据；2)调查从机载/空间/现场综合数据集中提取牧草生长和质量指标的业务职能，并制定牧草管理决策支持系统的框架；3)调查与小农接触的方法，并确定将这种技术及其产出纳入实践的态度和潜在障碍。该项目将提供新的数据，以确定对多源遥感和预测分析工具的能力的基线了解，以提供关于牧草数量和质量以及小农采用这种技术的能力和意愿的可靠和一致的信息。该项目的产出将直接为饲草生产管理活动提供信息，并将通过项目网站、项目结束讲习班以及在国际饲草业协会举办的进一步传播活动中进行宣传，传达给利益攸关方。

Agriculture and livestock production have historically been one of the major components of Colombian economic development and it is one of the top countries in the world in terms of greatest agricultural land expansion potential. Approximately 34% of the land area (~40m Ha) is used for livestock activities, with most pastures dedicated to extensive grazing systems. Agriculture is a critical source of employment in rural Colombia and is one of the sectors most affected by climate and climate change and where solutions to key challenges affecting the productivity and sustainability of pastures and the livestock sector are required. This collaborative project between University of Glasgow (UofG) University of Bristol (UofB) and CIAT will bring together cross-disciplinary perspectives and methodologies to develop RS-based approaches for forage monitoring and management at local and regional levels. The specific objectives are to: 1) develop co-designed work-flows for acquiring, processing and analysis of multi-dimensional multispectral and radar data for trial sites at CIAT headquarters; 2) investigate operational functions for extraction of grass growth and quality metrics from combined airborne/spaceborne/in situ datasets and develop a framework for a forage management decision support system; and 3) investigate methodologies for engagement with smallholders and determine attitudes to and potential barriers of incorporation of such technologies and their outputs into practice. The project will deliver new data to establish a baseline understanding of the capabilities of multi-source remote sensing and predictive analysis tools to provide reliable and consistent information on forage quantity and quality and smallholder capability and willingness to adopt such technologies. Outputs from the project will directly inform forage production management activities and will be communicated to stakeholders via a project website, an end-of-project workshop, and through promotion at further dissemination events run by CIAT.